Environmental Supply Chain Performance Mapping of an Enterprise by Exploring a Novel Vague-Intellectual Approach

Table 1

Conducted comprehensive/secondary systematic relevance in the context of GSCPM strategy, GTFN mathematical models, and degree of similarly mapping between the GTFN sets.

The authors	Their research contribution in the context of GSCP strategy
[48]	Introduced a mixed-integer linear programming-based framework for designing the sustainable SC. The proposed framework is explored to evaluate the tradeoffs between economic and environmental objective in case study of a firm. The results showed that the current legislation and the emission trading scheme must be strengthened and harmonized in order to drive a meaningful environmental strategy.
[49]	Used statistics package-based software for establishing the structural modeling of proposed green hypotheses and helping to analyze the performance mapping of sustainable material providers.
[50]	Developed an interpretive structural modeling to display the effects of GSCM drive over the performance of case study of a firm.
[51]	Identified the essential green manufacturing practices to build a GSCM framework, which is used for solving the supplier election problem in the context of Indian manufacturing industry. The relationships between the green supplier selection practices are studied.
[52]	Developed a GSCM framework by conducting the relevant literature survey in the context of GSCM from 2000 to 2010. The developed GSCM framework is used for measuring the GSC performance of a firm.
[53]	Applied a fuzzy-TOPSIS (technique for order preference similar to ideal solution) approach upon GSCM framework (included GSCM practices) for ranking the twelve suppliers. The obtained results are computed by fuzzy-TOPSIS and next compared with the ranks obtained by both the geometric mean and the graded mean methods for selection of the final supplier.
[54]	Developed a multicriteria decision-making hierarchical model (consisted of the traditional as well as green criteria) and implemented it along with an intellectual approach to evaluate the best green supplier for a Singapore-based plastic manufacturing company.
[55]	The empirical data were collected from members of NAPM (North American Portability Management) to know their awareness and frequent applications of “green” purchasing in their firms. They all suggested that environmental factor is a crucial factor in the supplier evaluation problem. Lastly, green purchasing was suggested as a powerful factor to reduce and eliminate the waste.
[56]	Recognized the twelve behavioral factors such as top management support, performance appraisal and reward, communication, green training, and employee empowerment in the context of mining GSCM. An interpretive structural modeling (ISM) has been explored to setup the interrelationships among the identified behavioral factors.
[20]	Presented an efficient supplier performance assessment index with GTFN set. A fuzzy overall evaluation index is estimated towards assessing the GSC performance of alternative suppliers.
[57]	Displayed that environmental metrics are key factors for evaluating, selecting, and maintaining any supplier. Case study of an auto industry is carried out to justify this assertion.
[58]	Highlighted and suggested a few factors, which may be considered as the initiatives of GSCM.
[59]	Developed a meditational regression model and applied it to find out the effect of green practices upon their interrelated practices. The model results depicted that supplier must be evaluated with cost and fast delivery with environmental concerns.
[60]	Proposed a double layers GSC efficient appraisement model for benchmarking the green alternative suppliers. A triangular fuzzy set is used to handle the vagueness associated with supplier’s model and select the most significant supplier.
[61]	Investigated the GSC as retailer strategy. It is found that GSC aids the retailer to improve their retailing profit with low promotional efforts.
[62]	Determined during a case study of coal enterprise of China that various driving mechanisms, i.e., government regulations, enterprise resource capability, and supply chain aid the global industries to reach to the green innovation.
[63]	Developed a multiobjective decision making hierarchical model, which included the forward and reverse logistic practices. The model is used to optimize and reduce the recycling as well as manufacturing cost.
[64]	Investigated the benefits of the green innovation policy and pricing strategy for remanufacturing system of a firm. After investigation, green innovation policy and pricing strategy are applied in purpose to determine the competitive advantage of them.
[65]	Proposed a hierarchical evaluation model (consist of green performance parameters) towards evaluating as well as selecting the alternative green vendor.
[66]	Proposed a dynamic integrated model with platform ecosystem framework (consisted by formal taxonomy indicators) to find the interrelationships across formal taxonomy indicators of platform ecosystem.
[67]	Analyzed the impact of an effort cost coefficient of low-carbon product advertising across the dual-channel SC. It is found that sharing ratio of low-carbon product advertising effort cost impacts on the profit of a dual-channel SC
[68]	Applied the differential game theory investment strategy over vertical incentive scheme of manufacturing and retailing sectors to analyze benefit of cost subsidy.
[69]	Proposed a new decision support system (GSCM framework with grey-Delphi approach) and applied it for evaluating and selecting the best and weak criteria from various criteria. It is suggested to oil and gas industry to improve its performance for weak criteria.
[70]	Applied knowledge-based network for analyzing the impact of association among strategy, intellectual capital, and network and finance over organizational performance of Brazilian small- and medium-sized enterprise.
[71]	Applied the four techniques, i.e., statistics, machine learning, data mining, and optimization to map the GSCM performance of supplier organizations under internal environment management, green purchasing, customer green cooperation, and general criteria.
[72]	Proposed and applied a three-path group decision making technique with decision-theoretic rough set (DTRS) as well as hesitant fuzzy linguistic (HFL) to solve the green vendor evaluation and selection problem. The results explicated that proposed techniques can well handle the expert’s assessment.
[73]	Built a judgment making decisional model to appraise the value of green suppliers under law and risk parameters. The proposed model enabled the organizations for managing the GSC. The authors extended research work with framing a new vague set-based approach for recognizing and predicting the relationships amongst the green supply risk parameters.
[74]	Conducted the relevant literature survey in the context of SCM and identified SC research areas, relationships among SC indicators, and emerging topics of SC.
[75]	Constructed the three pricing models and analyzed them simultaneously by changing the optimal profits of SC members and the optimal GSC degree of complementary products.
[76]	Identified the relationships among the green logistic operations, national economic, and environmental indicators and also ranked the best logistic countries over the period from 2007 to 2018.
[77]	Conducted the significant literature review on industry 4.0 SC strategies and identified and proposed the six research categories of industry 4.0 SC strategies with future research directions.
[78]	Recognized the vital relationship between the waste management practices and sustainability. The authors also evaluated the cause and effect relationship between them by using decision-making trial and evaluation laboratory (DEMATEL) approach.
[79]	Explored the qualitative survey to acquire in-depth knowledge by interviews against multisector organizations, which enable the authors to propose the areas where eco-innovation needs to be performed.
[80]	Proposed an integrated framework including digital project-driven supply chains (PDSC) indicators used to solve the multiple objective problems of architecture, engineering, construction, and operations and maintenance (AECOM) value chain.
[81]	Presented a summary of existing literature survey conducted over on machine learning (ML) in logistics and supply chain management (LSCM). It is concluded after analyzing the current literature, data, contemporary concepts, and gaps that suggested that LSCM must be intensified towards future researchers for research.
[82]	Audited the merged effect of internal environmental management (IEM) and green human resource management (GHRM) for corporate reputation (CR), environmental performance (EP), and financial performance (FP). The further indirect effects of CR and EP are analyzed.
[83]	Extracted the data from 76 commercial banks of four countries, i.e., Pakistan, India, Bangladesh, and Sri Lanka for the period 2009–2018. The generalized method of moments (GMM) is used to analyze the results. It is found that supply chain always encompasses the risk variables and is covered by qualitative assessment.
The authors	Their research works related to measure the degree of similarly between GTFN sets.
[33]	Proposed a novel fuzzy set-based intellectual technique to map the degree of similarity between the two generalized fuzzy sets. The similarity was measured from the center of gravity points of trapezoidal to triangular generalized fuzzy sets.
[34]	Measured the similarity between the two GTFN sets by merging the concept of left and right apex angles with center of gravity. The similarly between the two GTFN sets are mapped based on area, perimeter, and height.
[35]	Developed a new fuzzy based arithmetical approach considering the least number of parameters for computing the degree of similarity between the two GTFN sets.
[36]	Merged the idea of the predictable interval with dice similarity measure of two vectors for calculating the degree of similarity between the two GTFN sets.
[37]	Proposed a new degree of similarity concept, which measured the centers of gravity and the geometric distance between the two GTFN sets.
[38]	Proposed a multicriteria decision making appraisement model (consist of green-lean-agile logistic activities) with fuzzy performance index approach to assess the overall performance of a firm.
[39]	Identified that the domestic smog adversely impact the environment. The authors proposed a mathematical method to analyze this problem and provided the multiple solutions to minimize the smog pollutions.
[40]	Conducted the relevant literature survey in the extent of logistic 4.0 sustainability to overcome the vagueness of identified previous research gaps. The literature assisted the authors to propose a framework for measuring the logistic, sustainability, and technological adaptation of a warehouse.
[19]	Presented a framework consisted of 25 drivers linked with 8 criteria for analyzing the performance of a smart manufacturing firm. An integrated grey technique for order preference by similarity to ideal solution (Grey-TOPSIS) is implicated to rank the drivers. The obtained ranking is also validated using “complex proportional assessment or grey (COPRAS-G)” approach.